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School of Biological and Behavioural Sciences

Individual differences in artificial face perception

Project Overview

This project will investigate how humans perceive real and artificial faces and images, for example faces manipulated by AI such as Deepfakes, AI generated faces and images, and humanoid robots.

Deepfakes (images and videos that are manipulated to impersonate a real person or event) and AI-generated images (those that are generated in entirety by AI) – are becoming increasingly common. The use of these images has far-reaching consequences, from attempted election manipulation to blackmail and fraud. Sometimes it’s easy to spot a deepfake or an AI generated image, but as the technology for creating them becomes more sophisticated, detecting deepfakes is becoming more difficult. But what determines how one person might detect a deepfake or AI generated image, while another individual might not?

People vary widely in their ability to perceive, recognise, and remember real faces, and this project aims to investigate how and why people differ in their perception of artificial faces. We will use behavioural, psychophysical and eye-tracking measures to determine what underlies individual differences in deepfake and artificial image perception.

Research Environment

The Stewart Lab studies how humans perceive the world, make eye movements, and use visual information from across the visual field to inform our decisions and choices. Research in the lab uses behavioural and psychophysical experiments coupled with eye and hand movements, computational modelling, computer graphics, and statistical modelling, and successful candidates will receive training in these experimental and analysis methods. We have international links and active collaborations all over the world (USA, Germany, Australia, Canada, UK). You can find out more at www.emmaemstewart.com.

Find out more about the School of Biological and Behavioural Sciences on our website.

Keywords: Eye movements; Perception; Vision; Cognition; Behaviour; AI

Entry Requirements

We are looking for candidates to have or expecting to receive a first or upper-second class honours degree and a Master’s degree in an area relevant to the project such as Psychology or Neuroscience. Candidates with a degree in Biology, Mathematics, Computer Sciences or Engineering will also be considered.

Knowledge of programming (i.e. Matlab, R, Python), psychophysics, eyetracking, computer graphics (i.e. mesh manipulation in Blender), or running online experiments (for example using JsPsych) would be highly advantageous but are not required.

You must meet the IELTS requirements for your course and upload evidence before CSC’s application deadline, ideally by 1st March 2025. You are therefore strongly advised to sit an approved English Language test as soon as possible, where your IELTS test must still be valid when you enrol for the programme.

Please find further details on our English Language requirements page.

How to Apply

Formal applications must be submitted through our online form by 29th January 2025 for consideration. Please identify yourself as a ‘CSC Scholar’ in the funding section of the application.

Applicants are required to submit the following documents:

  • Your CV
  • Personal Statement
  • Evidence of English Language e.g.) IELTS Certificate
  • Copies of academic transcripts and degree certificates
  • References

Find out more about our application process on our SBBS website.

Informal enquiries about the project can be sent to Dr Emma Stewart AT emma.stewart@qmul.ac.uk Admissions-related queries can be sent to sbbs-pgadmissions@qmul.ac.uk

Shortlisted applicants will be invited for a formal interview by the supervisor. If you are successful in your QMUL application, then you will be issued an QMUL Offer Letter, conditional on securing a CSC scholarship along with academic conditions still required to meet our entry requirements.

Once applicants have obtained their QMUL Offer Letter, they should then apply to CSC for the scholarship with the support of the supervisor.

For further information, please go to the QMUL China Scholarship Council webpage.

Apply Online

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